• DocumentCode
    772513
  • Title

    Intelligent-memory architecture for artificial neural networks

  • Author

    Büddefeld, Jürgen ; Grosspietsch, Karl E.

  • Volume
    22
  • Issue
    3
  • fYear
    2002
  • Firstpage
    32
  • Lastpage
    40
  • Abstract
    Execution of artificial neural networks, especially for online pattern recognition, mainly depends on time-efficient execution of weighted sums. A new architecture achieves this goal, with a computation time superior to the time complexity of sequential von Neumann machines. This architecture uses additional logic to extend the functionality of conventional RAM. The authors discuss an implementation of this architecture that uses reconfigurable logic
  • Keywords
    backpropagation; neural chips; neural net architecture; pattern recognition; random-access storage; RAM structure; backpropagation; intelligent memory; learning mode; neural architectures; neural networks; pattern recognition; Artificial intelligence; Artificial neural networks; Computer architecture; Intelligent networks; Logic arrays; Machine intelligence; Parallel processing; Pattern recognition; Random access memory; Reconfigurable logic;
  • fLanguage
    English
  • Journal_Title
    Micro, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1732
  • Type

    jour

  • DOI
    10.1109/MM.2002.1013302
  • Filename
    1013302
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=772513